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Using SiteScope for "On-Premise Monitoring" with StormRunner Load

In order to adequately assess what’s happening to the underlying Infrastructure/Hardware during a performance test, monitoring is essential. Here at Trust IV, we decided to integrate HP’s SiteScope product into HP’s new cloud performance testing offering, StormRunner Load.

This is how I setup the Infrastructure.

1. Following the steps below, I created a SiteScope Server in our Internal Demo Network, behind the Trust IV firewall. This Sitescope server was configured with both Windows and UNIX/Linux monitoring groups and configured to monitor our application under test. 

  1. SiteScope software was installed.
  2. Configured Firewall Rules.
  3. Windows and UNIX/Linux Remote Servers were connected.
  4. Windows and UNIX/Linux monitoring groups were setup (Database Server, CPU, Memory, PING and Webserver).
  5. Within SiteScope I configured the optional "Generic Data Integration" pointing to the Receiver URL on the StormRunner Agent machine.

2.      I created a StormRunner Agent machine in our test network to receive the monitoring data from SiteScope and push that data to StormRunner Load.

  1. Node.js was installed
  2. SiteScope Agent software was installed
  3. Configured Firewall Rules
  4. I configured the SiteScope Agent to connect to our StormRunner Load account using the Key, Protocol, Username, Password, Tenant ID, Port and Proxy Details

3.       The SiteScope Agent asset was added into the Assets Monitors in StormRunner Load.

  1. I logged into StormRunner Load
  2. I added a new SiteScope-on-Premise monitor into the Assets>Monitors area. (This option isn't available unless StormRunner has detected communication from the local agent)
  3. I added the monitor to a Load Test

By implementing the SiteScope on-premise monitoring solution with integration into StormRunner Load, visibility of the application under test's (AUT) underlying Hardware/Infrastructure performance is improved. This provides valuable information, helping testers to identify performance bottlenecks during test execution.

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